1. Demographics, Human Capital, and the Demand for Housing Piet Eichholtz Maastricht University Thies Lindenthal Maastricht University ICPM Netspar Conference Maastricht University, 30 October 2007

2. in % > 20 15-25 15/5 5/0 0/–5 –5/–10 –10/–15 –15/–20 <–20% Source: United Nations Expected change in total population, 2005-2050 Large differences across Europe

3. Housing performance and demographic contraction Limburg is lagging behind the national trend

4. Shrinking Amsterdam Population decline 1795-1814 drove down house prices and rents

5. Structure of presentation Introduction Method and Data Results Conclusion

6. Intention of the paper is to understand (future) housing demand better How do demographic changes influence the demand for residential real estate? Will demand for housing decline when population growth slows down and societies become older? This paper contributes to the discussion in three ways –Refined methodology –Very detailed and high-quality data –European evidence

7. Preview of results Demographics impact the demand for housing –Human capital is one of the key drivers Education, income, health, employment status –Housing demand does not decline with age, but increases Positive human capital effects get stronger with age Aging and slowdown in population growth do not necessarily imply a decline in overall housing demand Education effect may even offset shrinking population

8. Literature Review The first wave of research Mankiw and Weil (1989) started the debate claiming that aging baby boomers will demand less housing in the future –They predicted house price drop of 47% Intense criticism by (inter alia) Peek and Wilcox (1991), Hendershott (1992), Engelhardt and Poterba (1991) Green and Hendershott (1996) find housing demand to stay constant with age –Education is main driver of demand

9. International evidence Good empirical studies are still very scarce England: Ermisch (1996) –Demand partly explained by demographics Japan: Ohtake and Shintani (1996) –Short run price effects of demographics, long run supply adjustment Sweden/OECD: Lindh and Malmberg (1999) –Demographics explain new construction in Sweden and OECD Austria: Lee et al. (2001) –Number of households is important The Netherlands: Neuteboom and Brounen (2007) –Demand for housing will not go down in aging society (due to cohort effects)

10. Agenda Introduction Method and Data Results Conclusion

11. First decompose, then predict demand for housing Control for housing quality and the demographic profile of household 1.Decompose house into housing services 2.Investigate willingness to pay for these services 3.Investigate the role of household’s demographic situation and human capital 4.Define a constant quality house 5.Calculate the willingness to pay for this house as a household becomes older 6.Predict housing demand with changing demographics

12. Refining the methodology Cohort variables versus life-cycle variables Cohort variables do not change when households grow older –Gender, ethnicity, education, birth-cohort –Mankiw and Weil: these variables change as households age Life-cycle variables depend on the household's position in life-cycle –Household size, employment status, income, health of household members –We take age as a proxy for the position in the life-cycle –Explicitly model income differences over time –Green and Hendershott: these variables are constant as households age

13. English Housing Condition Survey (EHCS) Covers both housing data and demographic information British government collected data on the current housing stock –Study provides a representative cross-section of households and their houses –We use the 2001 cross-section Excellent level of detail and quality of data –More than 900 variables, 17,500 households –Housing characteristics and values from professional inspections of dwellings –Information on household based on interviews Subsidies distort picture: exclude all subsidized housing, 10,000 left

14. Agenda Introduction Method and Data Results Conclusion

15. Hedonic regression: dwelling related variables How much are the components of a dwelling worth on average?

16. Hedonic regression: location related variables How much are the components of a dwelling on average worth?

17. Demographic regression Controlling for household size and income

18. Demand increases with education Additional educational achievement drives up reservation prices

19. Impairments to human wealth drive down demand Negative impact of disabilities, long-term illnesses, and children

20. Additional results of the demographic regression Importance of education increases with age –Older university graduates willing to pay more than younger ones No results for age and health –Analysis of the interaction terms for age and chronic illness, and for age and disability does not yield any significant results Full time employment –Drives down willingness to pay

21. Recap of the demographic regression results Willingness to pay for housing –Increases with household size and income –Decreases with children Human capital is key driver of demand –Education drives up demand –Chronic health problems and disabilities decrease demand Age has positive effect on demand –Age-income effect is positive –Age-education effect is positive When calculating future housing demand, the dynamics of these variables must be considered –Cohort variables vs. life-cycle variables

22. Household's willingness to pay for constant quality house Overall, demand is upward sloping as households become older

23. Demand for different dwelling types Upward-sloping with age for all types Detached houses and bungalows steepest increase

24. Similar demand growth for the English population scenarios Based on different assumptions fertility, migration, and life expectancy

25. Will higher demand translate into higher prices? Malpezzi and Maclennan (2001) find supply elasticities between 0 and 1 for post-war UK –The range depends on the assumptions for their models Office of the Deputy Prime Minister projects housing shortages if supply remains at current level

26. Agenda Introduction Method andData Results Conclusion

27. Demographics influence the demand for housing –Education, income, health, employment status, and household size are main drivers –Housing demand does not decline with age, but increases A slowdown in population growth (or even a shrinkage) does not necessarily imply a decline in overall demand –Human capital will keep on increasing –Younger generations better educated –Improving health Study provides analytical framework to apply to other (European) countries and regions Housing remains key asset in private retirement portfolio